the interpretation of data is tainted byself-interest.”One of the most common pitfalls, ac-cording to Lee, a member of the ResponseAdvisory Board, is incorrectly tagging achannel or platform with a sale and notattributing the appropriate acquisitioncosts.

“This can easily lead a marketer tomake poor decisions rather than correctattribution that will lead to an optimizedcampaign,” says Lee. “What’s importantto monitor are the device metrics aloneand then together as a strategic indicator.For example, by looking at conversionanalysis for mobile, it is important togauge how many consumers called from amobile device after visiting the site versushow many mobile consumers went to thesite and didn’t call. Also, of note, manyconsumers use a bookmark to click andAnother pro tip for understandingthe relationship between user activity onvarious devices?

“Monitoring and looking at how manyleads convert and if they are profitable —Understanding the limitations of thedata is also one of the most importancefactors in determining how to evaluate it.

“My experience is that the biggestchallenge to measuring across platformsis that exposure is defined differentlyon each platform and even within eachplatform,” says Hanley. “The simplisticway is to assume every medium can beevaluated similarly — and in doing thatyou can cannibalize a certain mediumbecause you suppress granular data inorder to make it comparable to some-thing else. The only way to avoid thattoday would be for the overall mediaindustry to agree on a common defini-tion of exposure. Minimally, the varyingdefinitions of exposure by platform needto be taken into account and somehowmade comparable.”

Making It CountThough much has progressed in theway performance marketers collect andutilize data across various channels, thegoals are ultimately the same: return oninvestment — and whatever the cli-ent’s other goals may be.“With retail, we tend to start at thevery broad high level,” says Garnett.“We want to look at gross retail num-bers by day up against media spendingbecause that’s staying at the level ofwhat really matters. From there we’lldrill down, and you won’t see every-thing in that data, but you’ll see somethings so you’ll follow a clue. Thisspending happened here and a week➜TV Time, an app with about 1 million dailyactive users, is just now beginning to mine itsexpanding viewer behavior data and make itavailable to networks, studios, and streamingvideo services — a possible boon for salesattribution technology.